Development of an Objective Measure of Infant Crying

婴儿哭泣客观测量方法的开发

• 批准号: 7595133
• 负责人: Tracy Kathleen Magee
• 金额: $ 7.55万
• 依托单位: UNIVERSITY OF ILLINOIS AT CHICAGO
• 依托单位国家: 美国
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-04-01 至 2011-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7595133
• 关键词: Abdominal colic; Affect; Agreement; Algorithms; Anxiety; Behavior; Characteristics; Communication; Computers; Crying; Data; Data Analyses; Decision Making; Development; Diagnosis; Diagnostic; Distress; Event; Evidence based intervention; Family; Frequencies; Fuzzy Logic; Goals; Hearing; Home environment; Hour; Human; Infant; Infantile Colic; Intervention; Judgment; Length; Life; Manuals; Measurement; Measures; Methods; Modeling; Monitor; Mothers; Newborn Infant; Outcome; Output; Parents; Pattern; Perception; Phase; Phase II Clinical Trials; Pilot Projects; Printing; Procedures; Process; Production; Research; Research Training; Risk; Shaken baby syndrome; Signal Transduction; System; Testing; United States National Institutes of Health; Writing; base; child physical abuse; computer generated; computerized; cost; diaries; digital; effective intervention; indexing; infancy; parental influence; prevent; sound; vocalization

DESCRIPTION (provided by applicant): Relevance: While colic, excessive crying in an otherwise well infant, affects approximately 10% of newborns, crying, the most common complaint of parents in the first year of life affects up to 40% of families. The problem is that the current approach to the diagnosis of colic and the outcomes of colic research are based on subjective data or parental perception of excessive crying via a written cry diary. Recent research suggests that parent perception of infant crying might be influenced by personal characteristics of the parent. Research also suggests that infants diagnosed with colic may have additional features such as unique cry characteristics which may contribute to perceptions that the cry is excessive. At present, there is no commonly used objective measure of infant crying. To better understand the differentiation between normal crying and colic, an objective measure of infant crying is needed. Purpose: This project is the second part of a multi-phased project that will develop and test a procedure for the analysis of infant vocalization to differentiate a normal cry and a colic cry. The first phase of the project tested the feasibility of acquiring infantile vocalization in normal infants in the home over a 24-hour period with a small, portable and commercially available digital recording system. In addition we determined that the recording system was acceptable to parents, did not interfere with daily activities of the mother or the infant or with mother-infant interactions. Data obtained from this study will be instrumental in the submission of a larger NIH application that will test our automated methods of analysis of infantile vocalization and differentiate perceived excessive crying from colic. Methods: In the next phase of this research we propose to use sound data collected in the home (20 parent- infant dyads) to evolve and test a model focused on automated analysis of crying as normal or colic. The aim of this pilot study is to validate the accuracy of our computerized method of sound data analysis that will identify characteristics of infant vocalizations that are associated with infant crying and produce an automated cry diary (i.e., a readable data print out of cry characteristics)

描述(申请人提供)：虽然绞痛，一个身体状况良好的婴儿过度哭闹，会影响大约10%的新生儿哭泣，但父母在出生第一年最常见的抱怨影响到高达40%的家庭。问题是，目前诊断绞痛的方法和绞痛研究的结果都是基于主观数据或父母通过书面哭泣日记对过度哭泣的感知。最近的研究表明，父母对婴儿哭闹的感知可能会受到父母的个人特征的影响。研究还表明，被诊断为绞痛的婴儿可能有其他特征，如独特的哭闹特征，这可能会导致人们认为哭声过大。目前，还没有一个普遍使用的客观衡量婴儿哭闹的标准。为了更好地理解正常哭闹和绞痛之间的区别，需要对婴儿哭闹进行客观测量。目的：这个项目是一个多阶段项目的第二部分，该项目将开发和测试一种分析婴儿发声的程序，以区分正常哭声和绞痛哭声。该项目的第一阶段测试了在家中使用小型、便携式和商用数字录音系统在24小时内获得正常婴儿发声的可行性。此外，我们确定记录系统对父母来说是可以接受的，不会干扰母亲或婴儿的日常活动或母婴互动。从这项研究中获得的数据将有助于提交更大的NIH申请，该申请将测试我们分析婴儿发声的自动化方法，并区分感知到的过度哭泣和绞痛。方法：在这项研究的下一阶段，我们建议使用在家中收集的声音数据(20个父母-婴儿二人组)来发展和测试一个专注于将哭声作为正常或绞痛的自动分析的模型。这项初步研究的目的是验证我们的计算机声音数据分析方法的准确性，该方法将识别与婴儿哭声有关的婴儿发声特征，并产生自动哭声日记(即，根据哭声特征打印的可读数据)。